CN111106859B - Millimeter wave/terahertz network large-scale MIMO wireless transmission method - Google Patents

Millimeter wave/terahertz network large-scale MIMO wireless transmission method Download PDF

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CN111106859B
CN111106859B CN201911188554.8A CN201911188554A CN111106859B CN 111106859 B CN111106859 B CN 111106859B CN 201911188554 A CN201911188554 A CN 201911188554A CN 111106859 B CN111106859 B CN 111106859B
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network
transmission
base station
user terminal
wireless transmission
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CN111106859A (en
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高西奇
尤力
陈旭
黄雨菲
石雪远
何思然
王闻今
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Southeast University
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W56/00Synchronisation arrangements
    • H04W56/004Synchronisation arrangements compensating for timing error of reception due to propagation delay
    • H04W56/005Synchronisation arrangements compensating for timing error of reception due to propagation delay compensating for timing error by adjustment in the receiver
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/02Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413MIMO systems
    • H04B7/0426Power distribution
    • H04B7/043Power distribution using best eigenmode, e.g. beam forming or beam steering
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/02Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413MIMO systems
    • H04B7/0452Multi-user MIMO systems
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/02Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0617Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L5/00Arrangements affording multiple use of the transmission path
    • H04L5/0001Arrangements for dividing the transmission path
    • H04L5/0014Three-dimensional division
    • H04L5/0023Time-frequency-space
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W52/00Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04TPC
    • H04W52/18TPC being performed according to specific parameters
    • H04W52/26TPC being performed according to specific parameters using transmission rate or quality of service QoS [Quality of Service]
    • H04W52/267TPC being performed according to specific parameters using transmission rate or quality of service QoS [Quality of Service] taking into account the information rate
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W52/00Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04TPC
    • H04W52/38TPC being performed in particular situations
    • H04W52/42TPC being performed in particular situations in systems with time, space, frequency or polarisation diversity
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W72/00Local resource management
    • H04W72/04Wireless resource allocation
    • H04W72/044Wireless resource allocation based on the type of the allocated resource
    • H04W72/0473Wireless resource allocation based on the type of the allocated resource the resource being transmission power
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/02Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413MIMO systems
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L5/00Arrangements affording multiple use of the transmission path
    • H04L5/003Arrangements for allocating sub-channels of the transmission path
    • H04L5/0037Inter-user or inter-terminal allocation

Abstract

The invention provides a millimeter wave/terahertz network large-scale MIMO wireless transmission method. In order to relieve the interruption effect of millimeter wave/terahertz frequency band transmission, a plurality of cells are combined into a wireless transmission network, each cell base station is provided with a large-scale antenna array, and a unitary transformation matrix is used for realizing large-scale beam coverage on user terminals in the whole network. Meanwhile, in order to alleviate the influence of multipath and Doppler effect on the transmission performance, the received signals are synchronized in time and frequency on each receiving beam of the user terminal. The method distributes the power of the transmitted signals according to the statistical information of the synchronized equivalent channels, and iteratively solves the optimal power distribution matrix based on the CCCP and the deterministic equivalent method. The invention effectively relieves the interrupt effect, multipath and Doppler effect in the wireless transmission process, and obviously reduces the complexity of the design of the millimeter wave/terahertz network large-scale MIMO transmission system sending signals and the information interaction overhead among cells.

Description

Millimeter wave/terahertz network large-scale MIMO wireless transmission method
Technical Field
The invention belongs to the field of communication, and particularly relates to a multi-cell wireless transmission method using a large-scale antenna array working in a millimeter wave/terahertz frequency band, in particular to a synchronization method suitable for the scene and a power distribution method based on the synchronization method and using statistical channel information to perform beam domain network transmission.
Background
A large-scale Multiple-Input Multiple-Output (MIMO) system base station uses a large-scale antenna array to simultaneously serve Multiple users, thereby effectively reducing inter-user interference and improving the spectrum utilization and power efficiency of a wireless communication system. Millimeter wave/terahertz communication has also been rapidly developed as another important technology by virtue of its advantages of wide bandwidth and narrow beam. The combination of massive MIMO and millimeter wave/terahertz communication is considered as a practical point of view, and has attracted attention. On one hand, the wavelength on the millimeter wave/terahertz frequency band is shorter, so that the base station and the user terminal can be configured with a large-scale antenna array. On the other hand, the beamforming gain brought by the large-scale MIMO can effectively solve the problem of high path loss in the millimeter wave/terahertz transmission process.
Millimeter wave/terahertz transmission not only adjusts the carrier frequency to the millimeter wave/terahertz frequency band, but also causes the performance bottleneck of the wireless transmission system due to the interruption effect of the millimeter wave/terahertz channel and the severe multipath and doppler effects in the transmission process. In order to alleviate the influence caused by channel interruption, a network transmission method can be adopted to combine a plurality of cells into one transmission network, and each base station can send signals to all user terminals in the network, so that the limitation that the base station can only communicate with the user terminals in the cells in the traditional multi-cell transmission method is broken through. A central controller is configured in the network, the central controller jointly designs the sending signals of all base stations according to the obtained channel information, and under the condition that channels of the base stations and cell user terminals are interrupted, other base stations in the network can communicate with the user, so that the communication requirement of the user terminals is ensured. In order to alleviate more serious multipath and doppler effects in the millimeter wave/terahertz transmission process, a synchronization method with better effect needs to be explored on the basis of traditional signal synchronization. In addition, the performance of system transmission depends on the quality of channel information acquired by the base station side to a great extent, instantaneous channel information acquisition is difficult in a large-scale MIMO transmission system, and especially in the network transmission process, the huge overhead of needing to exchange instantaneous channel information among cell base stations will seriously affect the system performance. In view of the above problems, the present invention provides a millimeter wave/terahertz network large-scale MIMO wireless transmission method, and in particular, relates to a signal synchronization method suitable for use in this scenario, and a power allocation method for performing beam-domain network wireless transmission using statistical channel information based on the synchronization method.
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to provide a network large-scale MIMO wireless transmission method working in a millimeter wave/terahertz frequency band so as to relieve the interruption effect, multipath and Doppler effect in the transmission process.
The technical scheme is as follows: in order to achieve the purpose, the invention adopts the technical scheme that:
a millimeter wave/terahertz network large-scale MIMO wireless transmission method comprises the following steps:
(1) each base station in the wireless transmission network is configured with a large-scale antenna array, the base station generates a large-scale beam set by using unitary transformation corresponding to the antenna array to cover the whole wireless transmission network, and each base station in the wireless transmission network performs beam domain wireless communication with each user terminal in the network on the generated beam;
(2) each user terminal individually estimates time and frequency adjustment parameters on each beam based on received synchronization signals transmitted from the base station;
(3) the user terminal independently performs time and frequency synchronization on the received signals based on the time and frequency adjustment parameter estimation value on each received beam, and the multipath and Doppler effect of the synchronized beam domain signals are effectively relieved, so that the signals are closer to the original beam domain signals sent by the base station;
(4) the base stations in the wireless transmission network acquire beam domain statistical channel information, the beam domain statistical channel information is sent to a network central controller through a return link, the central controller performs beam domain sending signal power distribution based on the beam domain statistical channel information, and power distribution results are sent to each base station through the return link;
(5) when the beam domain statistical channel information of the channel between the base station and the user terminal in the wireless network changes, the large-scale MIMO wireless transmission process of the network also changes dynamically.
In the step (1), each base station is configured with a large-scale antenna array. Each base station in the wireless transmission network generates a large-scale beam by using unitary transformation corresponding to each antenna array. The beam domain transform unitary matrix of each base station is uniquely determined and does not vary depending on the user terminal location and channel state. Compared with the existing multi-cell transmission method that the base station can only communicate with the user terminals in the cell, in order to relieve the problem of channel interruption of the millimeter wave/terahertz frequency band, each base station in the method can perform beam domain wireless communication with all the user terminals in a wireless transmission network.
In the step (2), for a single ue, the minimum time offset of the signal on the receiving beam is estimated according to the beam domain synchronization signal sent by the base station, and a target time compensation parameter is determined based on the estimated value of the time offset from the sending signal to the receiving beam of the ue, where the time compensation parameter is the minimum time offset of the signal on the receiving beam. For a single user terminal, estimating a minimum frequency offset and a maximum frequency offset of a signal on a receiving beam according to a beam domain synchronization signal transmitted by a base station, and determining a target frequency compensation parameter based on an estimated value of a frequency offset of a signal transmitted to the receiving beam of the user terminal, wherein the frequency compensation parameter is an average value of the minimum frequency offset and the maximum frequency offset of the signal on the receiving beam.
In the step (4), the power of the signal transmitted by each base station is designed by using the beam domain statistical channel information under the constraint condition of the transmission power of each base station and taking the maximum system network transmission and speed as a criterion. The beam domain channel refers to an equivalent beam domain channel obtained after the user terminal performs time domain and frequency domain synchronization on the signal on each receiving beam. The characteristic that the statistical channel information is irrelevant to the subcarriers can ensure that the designed sending signal is suitable for transmission on all subcarriers, thereby greatly reducing the complexity of transmission design.
In the step (4), the system network transmission sum rate is the sum of the traversal reachable transmission rates of all the user terminals in the system, and the transmission rate of each user terminal is expressed in a form of subtraction of two terms, wherein the first term is an expected expression of the entropy of the signal received by the user terminal and the interference plus noise, and the second term is an expression of the entropy of the interference plus noise received by the user terminal; power allocation is based on CCCP and deterministic equivalent methods to maximize system network transmission and rate.
The method for performing power allocation based on the CCCP and the deterministic equivalence method specifically comprises the following steps:
(a) and calculating the deterministic equivalent expression of the first item of the transmission rate of each user terminal in the system transmission and rate expression. And the deterministic equivalent auxiliary variable in the deterministic equivalent expression is obtained by iterative calculation convergence of the beam domain statistical channel information.
(b) And calculating the derivative of the second item of the transmission rate of each user terminal in the system transmission and rate expression with respect to the power distribution matrix to obtain the first-order Taylor series expansion of the second item of the expression. And replacing the second item of the transmission rate of each user terminal in the transmission and rate expression by the Taylor series expansion item to obtain the power distribution convex optimization problem.
(c) And obtaining a fraction equation equivalent to the convex optimization problem by using the KKT condition, and solving the fraction equation to obtain a beam domain power distribution matrix. The solution of the fractional equation may use newton's method, or other methods of solving the fractional equation.
(d) And recalculating by using the obtained power distribution matrix to obtain deterministic equivalent expression of a first term in the system network transmission and rate expression and Taylor series expansion of a second term in the expression, forming an updated convex optimization problem, and solving again. And (4) iteratively solving until the network transmission and the rate of the system converge, namely the difference between the system and the rate of the results of two iterations is less than a given threshold value.
In the step (5), the statistical channel information changes with the change of the millimeter wave/terahertz channel and the movement of the user terminal in the transmission network, and the base station acquires the statistical channel information at corresponding time intervals according to different scenes to dynamically realize beam domain power distribution.
Has the advantages that: compared with the prior art, the invention has the following advantages:
1. compared with the existing multi-cell transmission method, the invention combines a plurality of cells into one network, and the base station can communicate with all the user terminals in the wireless transmission network. When the channel between the base station and a user terminal in the network is interrupted, other base stations can communicate with the user terminal, and the characteristic can ensure the communication of the user terminal, so that the communication performance of the whole transmission network is improved.
2. Because the transmission performance is easily influenced by time and frequency expansion in the transmission process, the invention carries out the time synchronization and the frequency synchronization of signals on each receiving beam of the signals received by the user terminal, thereby effectively reducing the time and frequency expansion.
3. The statistical channel information is utilized to carry out transmission design, the required beam domain statistical channel information can be obtained through sparse detection signals, and the method is suitable for time division duplex and frequency division duplex systems. Meanwhile, due to the characteristic that the statistical channel information is irrelevant to the subcarriers, the transmission design result is suitable for each subcarrier, and the complexity of system transmission design is effectively reduced.
4. The iterative power allocation algorithm based on CCCP and determinacy equivalence can effectively reduce the complexity of physical layer realization and can obtain approximately optimal transmission performance.
Drawings
Fig. 1 is a flowchart of a millimeter wave/terahertz massive MIMO wireless transmission method.
Fig. 2 is a schematic diagram of a millimeter wave/terahertz network large-scale MIMO wireless transmission system.
Fig. 3 is a flowchart of an iterative algorithm based on CCCP and deterministic equivalence.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention.
As shown in fig. 1, the large-scale MIMO wireless transmission method for the millimeter wave/terahertz network disclosed in the embodiment of the present invention mainly includes the following steps:
(1) each base station in the wireless transmission network is configured with a large-scale antenna array, the base station generates a large-scale beam by using unitary transformation corresponding to the antenna array to cover the whole wireless transmission network, user terminals at different positions and in different directions in the transmission network are distinguished, and each base station in the wireless transmission network and each user terminal perform wireless communication in a beam domain;
(2) performing signal synchronization on each beam in a beam group of a user terminal separately; each user terminal individually estimates time and frequency adjustment parameters on each beam based on received synchronization signals transmitted from the base station;
(3) the user terminal independently performs time and frequency synchronization on the received signals based on the time and frequency adjustment parameter estimation value on each received beam, and the multipath and Doppler effect of the synchronized beam domain signals are effectively relieved, so that the signals are closer to the original beam domain signals sent by the base station;
(4) the base stations in the wireless transmission network acquire beam domain statistical channel information and send the statistical channel information to a network central controller through a return link, the central controller distributes beam domain sending signal power based on the statistical channel information and sends power distribution results to each base station through the return link;
(5) when the beam domain statistical channel information of the channel between the base station and the user terminal in the wireless network changes, the large-scale MIMO wireless transmission process of the network also changes dynamically.
In a preferred embodiment, the central controller utilizes the beam domain statistical channel information to design the transmission signal power of each base station under the constraint condition of the transmission power of each base station by taking the maximization of the transmission and the speed of the system network as a criterion. When designing an optimization problem, expressing the transmission rate of each user terminal as a subtraction form of two terms, wherein the transmission rate of a system network is the sum of the traversal reachable transmission rates of each user terminal in the system, the first term is an expected expression of the entropy of signals received by the user terminal and interference plus noise, and the second term is an expression of the entropy of the interference plus noise received by the user terminal; and then, performing power distribution based on a CCCP and deterministic equivalence method, specifically comprising the following steps:
(a) and calculating the deterministic equivalent expression of the first item of the transmission rate of each user terminal in the system transmission and rate expression. And the deterministic equivalent auxiliary variable in the deterministic equivalent expression is obtained by iterative calculation convergence of the beam domain statistical channel information.
(b) And calculating the derivative of the second item of the transmission rate of each user terminal in the system transmission and rate expression with respect to the power distribution matrix to obtain the first-order Taylor series expansion of the second item of the expression. And replacing the second item of the transmission rate of each user terminal in the transmission and rate expression by the Taylor series expansion item to obtain the power distribution convex optimization problem.
(c) And obtaining a fraction equation equivalent to the convex optimization problem by using the KKT condition, and solving the fraction equation to obtain a beam domain power distribution matrix. The solution of the fractional equation may use newton's method, or other methods of solving the fractional equation.
(d) And recalculating by using the obtained power distribution matrix to obtain deterministic equivalent expression of a first term in the system network transmission and rate expression and Taylor series expansion of a second term in the expression, forming an updated convex optimization problem, and solving again. And (4) iteratively solving until the network transmission and the rate of the system converge, namely the difference between the system and the rate of the results of two iterations is less than a given threshold value.
The following describes specific steps of the embodiment of the present invention with reference to specific scenarios:
1. system configuration
Taking the millimeter wave/terahertz network massive MIMO wireless transmission system shown in fig. 2 as an example, the system is a network formed by U cells, and each cell U e { 1.... multidot.u } includes a base station and KuThe system comprises a network central controller. Base station configuration in cell u
Figure BDA0002292994750000061
The antenna uniform area array has the antenna unit spacing in the horizontal direction and the vertical direction of half-wavelength order, wherein
Figure BDA0002292994750000062
And
Figure BDA0002292994750000063
the number of antennas in the horizontal dimension and the vertical dimension of the area array respectively. A set of user terminals { (K, U) | U { (K, U) | 1uN is configured for each user terminal (k, u)k,uThe half-wavelength uniform linear array of the antenna. In contrast to the general transmission method, each base station in the transmission network can communicate with each user terminal (k, u) in the network. The base station generates a large-scale beam to cover the whole transmission network through analog or digital or mixed beam forming. In this embodiment, the base station antennas have the same topology, so a uniform unitary transformation matrix can be used to transform the spatial domain signals to the beam domain, and transmit the signals to the user terminals in the beam domain. The present embodiment adopts an Orthogonal Frequency Division Multiplexing (OFDM) wideband modulation scheme based on cyclic prefix.
2. Beam-by-beam time-frequency synchronization
Note Hk,u,v(t, f) is a complex baseband downlink antenna domain channel response matrix from a base station to a user terminal (k, u) in the vth cell at time t and frequency f, and the dimension is Nk,u×Mv,MvIs the number of antennas of the base station (base station v) in the vth cell. The corresponding beam domain channel response matrix can be expressed as
Figure BDA0002292994750000064
Wherein Vk,uAnd UvAre the determination matrices, i.e. the beamforming matrices at the user terminal side and at the base station side, respectively, depending on the array topology at the user terminal (k, u) and at the base station v side. Wherein, when the half-wavelength uniform area array is configured at the base station side and the half-wavelength uniform linear array is configured at the user terminal side,
Figure BDA0002292994750000065
FMan M x M Discrete Fourier Transform (DFT) matrix,
Figure BDA0002292994750000066
the kronecker product of the matrix is represented,
Figure BDA0002292994750000067
and
Figure BDA0002292994750000068
the antenna numbers of the horizontal dimension and the vertical dimension of the base station v-plane array are respectively.
Since the frequency spreading caused by multipath time spreading and doppler spreading affects the transmission performance of the OFDM system, we need to perform time-frequency synchronization on the received signals. Different from the antenna domain synchronization method which adopts the same time-frequency synchronization parameter on different antennas, the received beam domain signals are synchronized on each receiving beam of the user terminal, so that the multipath effect and Doppler spread of a channel are relieved. The specific implementation mode is as follows:
the base station side periodically sends a synchronization signal, the user terminal can obtain time delay expansion caused by multipath effect and frequency expansion caused by Doppler effect by utilizing the existing estimation method, such as least power (LS) estimation, according to the synchronization signal received by each wave beam, then determines the minimum time offset, the minimum frequency offset and the maximum frequency offset on the wave beam to obtain wave beam domain time and frequency synchronization parameters, and then implements time frequency synchronization on the received signal on each received wave beam. The minimum time offset on the ith beam of the user terminal (k, u) is
Figure BDA0002292994750000071
Minimum and maximum frequency offsets are respectively
Figure BDA0002292994750000072
And
Figure BDA0002292994750000073
the time and frequency compensation parameters on the ith beam of the user terminal (k, u) are respectively
Figure BDA0002292994750000074
And
Figure BDA0002292994750000075
remember yk,u,i(t) For the received signal of the ith beam of the user terminal (k, u), for yk,u,i(t) is added
Figure BDA0002292994750000076
Time compensation of
Figure BDA0002292994750000077
Frequency compensation of (2), the compensated signal being expressed as
Figure BDA0002292994750000078
Wherein exp {. is an exponential operation with a natural logarithm as the base,
Figure BDA00022929947500000712
is an imaginary unit, i.e.
Figure BDA0002292994750000079
The received signal vector after time-frequency synchronization of the user terminal (k, u) can be expressed as:
Figure BDA00022929947500000710
where T represents the transpose operation of the vector and matrix. By removing the cyclic prefix, DFT transform, etc., the demodulated signal of the user terminal (k, u) on the reception beam i, subcarrier s can be represented in the digital domain as:
Figure BDA00022929947500000711
wherein xv,sFor signals transmitted by base station v on the s-th subcarrier, TcIs the OFDM symbol length, Gk,u,v,sAnd after carrying out time-frequency synchronization beam by beam at the user terminal (k, u), carrying out equivalent beam domain channel matrix on the subcarrier s from the base station v to the user terminal (k, u). Statistical channel signalling from base station v to user terminal (k, u) on sub-carrier sInformation processing device
Figure BDA0002292994750000081
Where |, indicates the hadamard product of the matrix. Note that the statistical channel information is independent of the subcarriers, and the statistical channel information on each subcarrier is the same, so the subcarrier index s, i.e. Ω, can be omittedk,u,v=Ωk,u,v,s
3. Transmission signal design
The beam domain signal received by the user terminal (k, u) in this scenario can be represented as:
Figure BDA0002292994750000082
for simplicity, the OFDM symbol numbering and subcarrier numbering have been omitted from the above formulae. In the above formula xk,u,vIs that the dimension of the base station v sending to the user terminal (k, u) is MvX 1 beam domain signal vector, Gk,u,vIs the beam domain channel matrix, G, from the base station v to the user terminal (k, u)k,u=[Gk,u,1,Gk,u,2,...,Gk,u,U]Is rearranged into dimensions of beam domain channel matrix
Figure BDA0002292994750000083
The channel matrix of (a) is determined,
Figure BDA0002292994750000084
is rearranged into dimensions of beam domain transmission signals
Figure BDA0002292994750000085
Vector of (a), nk,uZero mean variance of σ2White noise of (2). In addition, defining beam domain statistical channel information
Figure BDA0002292994750000086
Suppose that the user terminal (k, u) looks at interference plus noise
Figure BDA0002292994750000087
Is Gaussian noise with variance of
Figure BDA0002292994750000088
Wherein
Figure BDA0002292994750000089
Represents Nk,u×Nk,uThe matrix of the unit is formed by a matrix of units,
Figure BDA00022929947500000810
is the rearranged transmission signal xi,jThe superscript H denotes the conjugate transpose of the matrix. The expression succinct redefines the Q,
Figure BDA00022929947500000811
the traversal achievable transmission rate of the user terminal (k, u) can be expressed as:
Figure BDA00022929947500000812
definition of
Figure BDA0002292994750000091
fk,u,2(Q)=logdet(Kk,u) (7)
The system network transmission and rate may be expressed as:
Figure BDA0002292994750000092
the transmission system transmits a signal covariance matrix to the beam domain according to a maximum system network transmission and rate criterion
Figure BDA0002292994750000093
Design is carried out, and a covariance matrix of the beam domain transmission signals is easy to obtain
Figure BDA0002292994750000094
The transmission performance is optimal when the array is diagonal. The design problem of the covariance matrix of the transmitted signals is simplified into the power distribution problem, so that the following optimization problems are obtained:
Figure BDA0002292994750000095
wherein, to redefine Q for conciseness of expression,
Figure BDA0002292994750000096
is a matrix of the power constraint of the auxiliary base station, diag {. is a vector diagonalization operation, PvIs the power constraint of base station v, tr (-) denotes the trace of the computation matrix, and > 0 denotes the matrix non-negative definite.
Because of the expected operational implications in computing system network transmission and rates, the channels need to be traversed using monte carlo simulations. In order to reduce the computational complexity, the present embodiment uses a large-dimensional random matrix theory to calculate the deterministic equivalence of the traversal reachable transmission rates of the ue. The method can obtain the approximation result of the system network transmission and the rate only by utilizing the statistical channel information. In addition, the objective function of the problem is not a convex function, so that a global optimal solution is difficult to obtain, and the solving complexity is high. To this end, the embodiment of the present invention further employs an iterative algorithm based on CCCP to solve the above optimization problem.
The specific implementation process of the algorithm is as follows:
step 1: initially designed transmit signal covariance matrix Q(0)The iteration number l is set to 0. At initialization of transmit signal covariance matrix Q(0)Uniform power allocation, or other power allocation methods, may be assumed.
Step 2: using Q(i)Deterministic equivalent auxiliary variable used for iterative computation of ith CCCP iteration
Figure BDA0002292994750000101
And phik,uUntil convergence
Figure BDA0002292994750000102
Figure BDA00022929947500001014
Superscript-1 denotes the matrix inversion operation, Ck,u(X) production of Nk,u×Nk,uA diagonal matrix of, and Bk,u(Y) production
Figure BDA0002292994750000103
The diagonal elements of (a) are represented as:
[Ck,u(X)]n,n=tr{diag{([Ωk,u]n,:)T}X} (12)
[Bk,u(Y)]m,m=tr{diag{([Ωk,u]:,m)}Y} (13)
wherein [ X ]]n,:Represents taking the n-th row of matrix X, [ X]:,mIndicating taking the mth column of matrix X.
And step 3: using deterministic equivalent auxiliary variables
Figure BDA0002292994750000104
And phik,uComputingk,uAnd
Figure BDA0002292994750000105
Figure BDA00022929947500001015
Figure BDA0002292994750000106
calculating the first item of the transmission rate of the user terminal in the first CCCP iteration
Figure BDA0002292994750000107
Certainty of identity
Figure BDA0002292994750000108
Figure BDA0002292994750000109
While the certainty of computing system network transmission and rate is equivalent:
Figure BDA00022929947500001010
and 4, step 4: calculating derivative terms to be used for the first CCCP iteration
Figure BDA00022929947500001011
As follows
Figure BDA00022929947500001012
Wherein
Figure BDA00022929947500001013
The following convex optimization problem of the current CCCP iteration is formed:
Figure BDA0002292994750000111
wherein
Figure BDA0002292994750000112
Figure BDA0002292994750000113
And 5: the optimization problem can be further reduced to
Figure BDA0002292994750000114
Obtaining a partial equation equivalent to (22) according to the KKT condition of the optimization problem
Figure BDA0002292994750000115
Lagrange multiplier
Figure BDA0002292994750000116
Satisfy the requirement of
Figure BDA0002292994750000117
In the formula (23), γk,u,m、λk,u,mk,u,mAnd
Figure BDA0002292994750000118
are respectively ask,u、Qk,u、Δk,uAnd
Figure BDA0002292994750000119
the m-th diagonal element of (a),
Figure BDA00022929947500001110
is composed of
Figure BDA00022929947500001111
The nth diagonal element of (2), the auxiliary variable
Figure BDA00022929947500001112
And set Sk,u,m,i,jAre respectively as
Figure BDA00022929947500001113
Figure BDA00022929947500001114
The solution of the fractional equation (23) may be newton's method, or other fractional equation solution methods.
Step 6: re-determinacy of equal auxiliary variable computation system network transmission and rate of determination of equal auxiliary variable based on solution of fractional equation (23)
Figure BDA0002292994750000121
And phik,uUntil convergence and computing deterministic equivalence of new system network transmissions and rates
Figure BDA0002292994750000122
And 7: comparing network transmissions and rate deterministic equivalents of the new system
Figure BDA0002292994750000123
And the calculation result of the last iteration
Figure BDA0002292994750000124
Stopping the iteration if the difference between the two is less than a given threshold, Q(l+1)Is the solution to the optimization problem. Otherwise, let l be l +1, and return to step 4.
The statistical channel information is irrelevant to the subcarriers, so the power distribution result is suitable for all the subcarriers, and the complexity of signal transmission design in the transmission process of the system is greatly reduced.
And in the moving process of the user terminal, the base station updates the power distribution result of the transmitted signal in real time along with the change of the beam domain statistical channel information. The change of the beam domain statistical channel information is related to a specific application scenario, a typical statistical time window is several times or tens of times of a short-time transmission time window, and the acquisition of the related statistical channel information is also performed on a larger time width.
It should be noted that the above mentioned embodiments are only specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of changes or substitutions within the technical scope of the present invention, and all such changes or substitutions should be covered by the scope of the present invention. All the components not specified in the present embodiment can be realized by the prior art.

Claims (7)

1. The millimeter wave/terahertz network large-scale MIMO wireless transmission method is characterized in that: the method comprises the following steps:
(1) each base station in the wireless transmission network is configured with a large-scale antenna array, the base station generates a large-scale beam set by using unitary transformation corresponding to the antenna array to cover the whole wireless transmission network, and each base station in the wireless transmission network performs beam domain wireless communication with each user terminal in the network on the generated beam;
(2) each user terminal respectively estimates time and frequency adjustment parameters on each wave beam based on the received synchronous signals transmitted from the base station;
(3) the user terminal respectively performs time and frequency synchronization on the received signals based on the time and frequency adjustment parameter estimation values on each receiving beam;
(4) each base station in the network sends the acquired beam domain statistical channel information to a central controller of the network, the central controller performs beam domain transmission signal power distribution based on the beam domain statistical channel information, and sends a power distribution result to each base station through a return link; the central controller utilizes the wave beam domain statistical channel information to design the signal transmitting power of each base station by taking the maximum system network transmission and speed as a criterion under the constraint condition of the transmitting power of each base station; the power distribution result of the transmitted signal is applied to all subcarriers;
the system network transmission and rate is the sum of the traversing reachable transmission rates of all user terminals in the system, and the transmission rate of each user terminal is expressed in a subtraction mode of two terms, wherein the first term is an expected expression of the entropy of signals received by the user terminal and interference plus noise, and the second term is an expression of the entropy of the interference plus noise received by the user terminal; performing power allocation based on CCCP and deterministic equivalence methods to maximize system network transmission and rate;
a set of user terminals { (K, U) | U { (K, U) | 1uThe system is a network formed by U cells, and each cell U belongs to { 1.... U } and comprises a base station and KuThe traversal achievable transmission rate of the user terminal (k, u) is expressed as:
Figure FDA0002688896670000011
wherein the content of the first and second substances,
Figure FDA0002688896670000012
Gk,u=[Gk,u,1,Gk,u,2,...,Gk,u,U]is rearranged into dimensions of beam domain channel matrix
Figure FDA0002688896670000013
Channel matrix of Gk,u,vIs the beam domain channel matrix from base station v to user terminal (k, U), v ∈ { 1.,. U }, MvIs the number of antennas of the base station in the vth cell,
Figure FDA0002688896670000014
represents Nk,u×Nk,uIdentity matrix, Nk,uThe number of antennas of the user terminal (k, u),
Figure FDA0002688896670000015
Figure FDA0002688896670000021
is rearranged into dimensions of beam domain transmission signals
Figure FDA0002688896670000022
Vector of (a), xk,u,vIs that the dimension of the base station v sending to the user terminal (k, u) is MvThe x 1 beam-domain signal vector is,
Figure FDA0002688896670000023
is the rearranged transmission signal xi,jCovariance matrix of σ2Is the variance of the noise;
(5) when the beam domain statistical channel information of the channel between the base station and the user terminal in the wireless network changes, the large-scale MIMO wireless transmission process of the network also changes dynamically.
2. The millimeter wave/terahertz network massive MIMO wireless transmission method according to claim 1, wherein: in the step (1), each base station is configured with a large-scale antenna array, each base station in the wireless transmission network generates a large-scale beam by using unitary transformation corresponding to the antenna array, and a beam domain transformation unitary matrix of each base station is uniquely determined and does not change due to the position of the user terminal and the channel state.
3. The millimeter wave/terahertz network massive MIMO wireless transmission method according to claim 2, wherein: the large-scale wave beams adopt millimeter wave/terahertz wave beams with the same preset frequency.
4. The millimeter wave/terahertz network massive MIMO wireless transmission method according to claim 1, wherein: in the step (2), for a single ue, the minimum time offset of the signal on the receiving beam is estimated according to the beam domain synchronization signal sent by the base station, and a target time compensation parameter is determined based on the estimated value of the time offset from the sending signal to the receiving beam of the ue, where the time compensation parameter is the minimum time offset of the signal on the receiving beam.
5. The millimeter wave/terahertz network massive MIMO wireless transmission method according to claim 1, wherein: in the step (2), for a single ue, according to the beam domain synchronization signal sent by the base station, the minimum frequency offset and the maximum frequency offset of the signal on the receiving beam are estimated, and a target frequency compensation parameter is determined based on the estimated value of the frequency offset of the signal sent to the ue receiving beam, where the frequency compensation parameter is an average value of the minimum frequency offset and the maximum frequency offset of the signal on the receiving beam.
6. The millimeter wave/terahertz network massive MIMO wireless transmission method according to claim 1, wherein: the method for performing power allocation based on the CCCP and the deterministic equivalence method comprises the following steps:
(a) calculating the deterministic equivalent expression of the first item of each user terminal transmission rate in the system network transmission and rate expression; the deterministic equivalence auxiliary variable in the deterministic equivalence expression is obtained by iterative computation convergence of beam domain statistical channel information;
(b) calculating the derivative of the second item of the transmission rate of each user terminal in the system transmission and rate expression with respect to the power distribution matrix to obtain first-order Taylor series expansion of the second item of the expression, and replacing the second item of the transmission rate of each user terminal in the transmission and rate expression with the Taylor series expansion item to obtain a power distribution convex optimization problem;
(c) obtaining a partial equation equivalent to the convex optimization problem by using the KKT condition, and solving the partial equation to obtain a beam domain power distribution matrix;
(d) recalculating by using the obtained power distribution matrix to obtain deterministic equivalent expression of a first term in the system transmission and speed expression and Taylor series expansion of a second term in the expression, forming an updated convex optimization problem, and solving again; and (4) iteratively solving until the system transmission and the rate converge, namely the difference between the system transmission and the rate of the two iteration results is less than a given threshold value.
7. The millimeter wave/terahertz network massive MIMO wireless transmission method according to claim 1, wherein: in the step (5), the statistical channel information changes with the change of the millimeter wave/terahertz channel and the movement of the user terminal in the transmission network, and the base station acquires the statistical channel information at corresponding time intervals according to different scenes to dynamically realize beam domain power distribution.
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Families Citing this family (19)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112533274B (en) * 2020-10-29 2021-08-20 北京科技大学 Indoor terahertz BWP and power scheduling method and device
CN113573361B (en) * 2021-06-22 2024-04-16 西安电子科技大学 Millimeter wave MEC-oriented low-delay high-rate unloading transmission method
CN113612558B (en) * 2021-08-03 2022-06-24 东南大学 Resource allocation method for maximizing spectral efficiency in terahertz communication system
CN113346960B (en) * 2021-08-05 2021-11-09 北京理工大学 Method and system for synthesizing and calibrating terahertz space quadrature modulation signals
CN113765567B (en) * 2021-09-08 2024-02-02 东南大学 Large-scale MIMO receiving and transmitting combined beam forming method based on deep learning
CN114172549B (en) * 2021-12-07 2022-06-24 东南大学 Sky wave large-scale MIMO communication downlink transmission method
CN114337851B (en) * 2021-12-21 2023-07-21 郑州大学 Intelligent super-surface-assisted terahertz safety communication method and device
CN114567384B (en) * 2022-02-17 2023-06-27 上海交通大学 Universal silicon-based photon millimeter wave/terahertz chip and transmission system and method thereof
CN114614869B (en) * 2022-03-09 2023-05-19 电子科技大学 Near-far field unified and controllable transmitting beam forming method in terahertz communication
CN114978355B (en) * 2022-04-11 2023-06-16 北京邮电大学 Terahertz link discovery method based on superheterodyne intermediate frequency leakage sensing
CN114826345A (en) * 2022-04-15 2022-07-29 南京邮电大学 Millimeter wave communication-based power distribution method in super-large-scale MIMO system
CN114650608B (en) * 2022-04-18 2023-04-07 南通大学 Multi-central processing unit cooperation method for removing cellular massive MIMO
CN114826349B (en) * 2022-04-19 2024-02-02 东南大学 Transmitting power minimization transmission method based on reconfigurable intelligent surface
CN114844538B (en) * 2022-04-29 2023-05-05 东南大学 Millimeter wave MIMO user increment cooperative beam selection method based on wide learning
CN115118315B (en) * 2022-06-15 2023-03-24 国家工业信息安全发展研究中心 Low-complexity communication network system, method and readable medium
CN115102589B (en) * 2022-06-29 2023-07-25 内蒙古大学 Deep learning hybrid precoding method of terahertz large-scale MIMO system
CN115225164B (en) * 2022-07-25 2023-07-21 西北工业大学深圳研究院 Non-orthogonal terahertz communication method and system based on intelligent reflecting surface
CN115801072B (en) * 2022-11-23 2024-04-02 东南大学 Analog-to-digital converter precision distribution method of network-assisted full duplex system
CN116318488A (en) * 2023-04-07 2023-06-23 昆明理工大学 Evaluation method for terahertz MIMO communication system in personnel-intensive places based on ray tracing

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105933979A (en) * 2016-04-12 2016-09-07 东南大学 Multi-cell BDMA (beam division multiple access) transmission power allocation method
CN108781459A (en) * 2016-03-11 2018-11-09 交互数字专利控股公司 Classification for the uplink multiuser transmission in WLAN and silence

Family Cites Families (19)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8363744B2 (en) * 2001-06-10 2013-01-29 Aloft Media, Llc Method and system for robust, secure, and high-efficiency voice and packet transmission over ad-hoc, mesh, and MIMO communication networks
US6956907B2 (en) * 2001-10-15 2005-10-18 Qualcomm, Incorporated Method and apparatus for determining power allocation in a MIMO communication system
US7020110B2 (en) * 2002-01-08 2006-03-28 Qualcomm Incorporated Resource allocation for MIMO-OFDM communication systems
US6862271B2 (en) * 2002-02-26 2005-03-01 Qualcomm Incorporated Multiple-input, multiple-output (MIMO) systems with multiple transmission modes
US8929550B2 (en) * 2013-02-01 2015-01-06 Department 13, LLC LPI/LPD communication systems
CN107438955B (en) * 2015-04-09 2020-11-06 三星电子株式会社 Method and apparatus for controlling transmission power in wireless communication system using multiple antennas
JP6543738B2 (en) * 2015-06-30 2019-07-10 ノキア ソリューションズ アンド ネットワークス オサケ ユキチュアNokia Solutions and Networks Oy Control signaling
US10595322B2 (en) * 2015-11-23 2020-03-17 Qualcomm Incorporated Beamforming and user equipment grouping
KR102461619B1 (en) * 2016-02-12 2022-11-02 삼성전자주식회사 Apparatus and method for beamforming in an wireless communication system
US10630410B2 (en) * 2016-05-13 2020-04-21 Telefonaktiebolaget Lm Ericsson (Publ) Network architecture, methods, and devices for a wireless communications network
US10367677B2 (en) * 2016-05-13 2019-07-30 Telefonaktiebolaget Lm Ericsson (Publ) Network architecture, methods, and devices for a wireless communications network
WO2018076362A1 (en) * 2016-10-31 2018-05-03 Southeast University Systems and methods for wireless communication with per-beam signal synchronization
US10736119B2 (en) * 2017-02-21 2020-08-04 Northwestern University Radio resource management in large wireless networks
CN108736939B (en) * 2017-04-13 2021-02-09 华为技术有限公司 Method and apparatus for beam training
US10425900B2 (en) * 2017-05-15 2019-09-24 Futurewei Technologies, Inc. System and method for wireless power control
KR102379822B1 (en) * 2017-06-15 2022-03-30 삼성전자 주식회사 Method and apparatus for controlling transmission power of a terminal in a beamforming system
US10797927B2 (en) * 2017-12-12 2020-10-06 Charter Communications Operating, Llc Methods and apparatus for supporting use of multiple beams for communications purposes
CA3067409A1 (en) * 2019-01-09 2020-07-09 Comcast Cable Communications, Llc Methods, devices, and apparatuses for beam management
CN110518961B (en) * 2019-08-29 2020-12-11 东南大学 Large-scale MIMO satellite mobile communication method and system

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108781459A (en) * 2016-03-11 2018-11-09 交互数字专利控股公司 Classification for the uplink multiuser transmission in WLAN and silence
CN105933979A (en) * 2016-04-12 2016-09-07 东南大学 Multi-cell BDMA (beam division multiple access) transmission power allocation method

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
《 基于导频复用的大规模MIMO无线传输理论方法研究》;尤力;《中国博士学位论文全文数据库》;20171231(第2期);第57、67页 *

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